Falls among the elderly, one of the most common reasons requiring medical intervention and a contributing factor in 40% of nursing home admissions, are a major health problem. Several studies have identified quantifiable gait markers that appear to distinguish between elderly "fallers" and non-fallers. These studies have relied on data acquired in gait-laboratories. Extending gait assessment capability, and falls detection, into the home could provide valuable before-the-fact information on gait weakness evolution, which in turn could be used to assess the efficiency of counter measures. Current mobile gait analysis techniques are insufficient because they rely on compliance or are too intrusive. The development of a new gait assessment and falls monitor is proposed. The device is passive, can transmit acquired data wirelessly, and obtains gait data from sensing floor vibrations, precluding the need to wear a device, walk on special surfaces or be observed by cameras. Its ability to detect different gait modes with high fidelity as well as differentiate between falling objects and simulated falls has been demonstrated. This study's principal aim is to validate the device's performance through a comparison with accepted gait assessment techniques at the Physical Medicine and Rehabilitation Gait lab at the University of Virginia Health System.